In [1]:

    

import numpy as np
import pandas as pd


    

In [2]:

    

df = pd.DataFrame(data=[[1, 2, 3], [4, 5, 6]], columns=['a', 'b', 'c'])
print(df)


    

    




   a  b  c
0  1  2  3
1  4  5  6

In [3]:

    

a_df = df.values
print(a_df)


    

    




[[1 2 3]
 [4 5 6]]

In [4]:

    

print(type(a_df))


    

    




<class 'numpy.ndarray'>

In [5]:

    

print(a_df.dtype)


    

    




int64

In [6]:

    

s = df['a']
print(s)


    

    




0    1
1    4
Name: a, dtype: int64

In [7]:

    

a_s = s.values
print(a_s)


    

    




[1 4]

In [8]:

    

print(type(a_s))


    

    




<class 'numpy.ndarray'>

In [9]:

    

print(a_s.dtype)


    

    




int64

In [10]:

    

df_f = pd.DataFrame([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
print(df_f)


    

    




     0    1    2
0  0.1  0.2  0.3
1  0.4  0.5  0.6

In [11]:

    

a_df_f = df_f.values
print(a_df_f)


    

    




[[0.1 0.2 0.3]
 [0.4 0.5 0.6]]

In [12]:

    

print(type(a_df_f))


    

    




<class 'numpy.ndarray'>

In [13]:

    

print(a_df_f.dtype)


    

    




float64

In [14]:

    

df_multi = pd.read_csv('data/src/sample_pandas_normal.csv')
print(df_multi)


    

    




      name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [15]:

    

a_df_multi = df_multi.values
print(a_df_multi)


    

    




[['Alice' 24 'NY' 64]
 ['Bob' 42 'CA' 92]
 ['Charlie' 18 'CA' 70]
 ['Dave' 68 'TX' 70]
 ['Ellen' 24 'CA' 88]
 ['Frank' 30 'NY' 57]]

In [16]:

    

print(type(a_df_multi))


    

    




<class 'numpy.ndarray'>

In [17]:

    

print(a_df_multi.dtype)


    

    




object

In [18]:

    

a_df_int = df_multi[['age', 'point']].values
print(a_df_int)


    

    




[[24 64]
 [42 92]
 [18 70]
 [68 70]
 [24 88]
 [30 57]]

In [19]:

    

print(type(a_df_int))


    

    




<class 'numpy.ndarray'>

In [20]:

    

print(a_df_int.dtype)


    

    




int64

In [21]:

    

print(a_df_int.T)


    

    




[[24 42 18 68 24 30]
 [64 92 70 70 88 57]]

In [22]:

    

a_df_int = df_multi.select_dtypes(include=int).values
print(a_df_int)


    

    




[[24 64]
 [42 92]
 [18 70]
 [68 70]
 [24 88]
 [30 57]]

In [23]:

    

print(type(a_df_int))


    

    




<class 'numpy.ndarray'>

In [24]:

    

print(a_df_int.dtype)


    

    




int64